Triple

T11968481
Position Surface form Disambiguated ID Type / Status
Subject Campo de Belchite comarca E284852 entity
Predicate contains P35 FINISHED
Object Lagata
Lagata is a small municipality in the province of Zaragoza, within the autonomous community of Aragon in northeastern Spain.
 E956350 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lagata | Statement: [Campo de Belchite comarca, contains, Lagata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lagata
Context triple: [Campo de Belchite comarca, contains, Lagata]
  • A. Laka
    Laka is a dialect of the Sara language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • B. Lagunna
    Lagunna is a titled chief within the Oyo Mesi, the council of kingmakers and principal nobles in the traditional Oyo Yoruba political system.
  • C. Pasay
    Pasay is a highly urbanized coastal city in the Philippines known for its entertainment complexes, shopping centers, and proximity to Manila’s main international airport.
  • D. Labuha
    Labuha is a coastal town that serves as an important local center on the Indonesian island of Halmahera.
  • E. Laja
    Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lagata
Triple: [Campo de Belchite comarca, contains, Lagata]
Generated description
Lagata is a small municipality in the province of Zaragoza, within the autonomous community of Aragon in northeastern Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lagata
Target entity description: Lagata is a small municipality in the province of Zaragoza, within the autonomous community of Aragon in northeastern Spain.
  • A. Laka
    Laka is a dialect of the Sara language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • B. Lagunna
    Lagunna is a titled chief within the Oyo Mesi, the council of kingmakers and principal nobles in the traditional Oyo Yoruba political system.
  • C. Pasay
    Pasay is a highly urbanized coastal city in the Philippines known for its entertainment complexes, shopping centers, and proximity to Manila’s main international airport.
  • D. Labuha
    Labuha is a coastal town that serves as an important local center on the Indonesian island of Halmahera.
  • E. Laja
    Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9037bee54819085242a3ef3e286f9 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459691ff0819099282172933d2d81 completed May 1, 2026, 7:42 a.m.
NEDg Description generation batch_69f4645ef63881909b46937f73d637a3 completed May 1, 2026, 8:29 a.m.
NED2 Entity disambiguation (via description) batch_69f465be4db08190882898a17d077019 completed May 1, 2026, 8:35 a.m.
Created at: April 8, 2026, 9:46 p.m.